Investigating the temporal pattern of neuroimaging-based brain age estimation as a biomarker for Alzheimer's Disease related neurodegeneration

• Published in: NeuroImage (Orlando, Fla.) Vol. 263; p. 119621
• Main Authors: Taylor, Alexei, Zhang, Fengqing, Niu, Xin, Heywood, Ashley, Stocks, Jane, Feng, Gangyi, Popuri, Karteek, Beg, Mirza Faisal, Wang, Lei
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.11.2022; Elsevier Limited; Elsevier
• Subjects: Age; Age determination; Aging; Alzheimer Disease - diagnostic imaging; Alzheimer's disease; Atrophy; Biomarkers; Brain - diagnostic imaging; Brain age estimation; Cognitive ability; Cognitive Dysfunction - diagnostic imaging; Cross-Sectional Studies; Datasets; Disease Progression; Humans; Investigations; Longitudinal analysis; Machine learning; Magnetic resonance imaging; Magnetic Resonance Imaging - methods; Medical imaging; Multimodal imaging; Neurodegeneration; Neurodegenerative diseases; Neuroimaging; Neuroimaging - methods; Brain age estimation; Longitudinal analysis; Multimodal imaging; Alzheimer's disease; Machine learning

•Combining multimodal imaging data to estimate brain age yields improved prediction performance than single modality on average.•Brain age gap is estimated to increase linearly across the 8-year follow-up.•Brain age gap of individuals with progressive mild cognitive impairment increases at a signifi...